Periodic Poisson Processes and Almost-lack-of-memory Distributions

Boyan N. Dimitrov; Vladimir Rykov; Zinovi L. Krougly

doi:10.1023/B:AURC.0000044269.32890.3e

Periodic Poisson Processes and Almost-lack-of-memory Distributions

Boyan N. Dimitrov, Vladimir Rykov, Zinovi L. Krougly

Kettering University

Research output: Contribution to journal › Article › peer-review

Abstract

<p> Certain characterization properties of time-varying periodic Poisson &fllig;ows are studiedin terms of almost-lack-of-memory (ALM) distributions. Parameter estimation formulas arederived. A method for verifying the hypothesis on the membership of a sample to the classof ALM-distributions is developed. Algorithms for computing critical levels and power of thelikelihood ratio test by the Monte Carlo method are designed.</p>

Original language	American English
Journal	Automation and Remote Control
Volume	65
DOIs	https://doi.org/10.1023/B:AURC.0000044269.32890.3e
State	Published - Oct 1 2004

Keywords

Mechanical Engineer
Parameter Estimation
Monte Carlo Method
Likelihood Ratio
System Theory

Disciplines

Mathematics

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10.1023/B:AURC.0000044269.32890.3eLicense: CC BY

https://link.springer.com/article/10.1023/B:AURC.0000044269.32890.3e

Cite this

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abstract = " Certain characterization properties of time-varying periodic Poisson &fllig;ows are studiedin terms of almost-lack-of-memory (ALM) distributions. Parameter estimation formulas arederived. A method for verifying the hypothesis on the membership of a sample to the classof ALM-distributions is developed. Algorithms for computing critical levels and power of thelikelihood ratio test by the Monte Carlo method are designed.",

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AU - Rykov, Vladimir

AU - Krougly, Zinovi L.

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Y1 - 2004/10/1

N2 - Certain characterization properties of time-varying periodic Poisson &fllig;ows are studiedin terms of almost-lack-of-memory (ALM) distributions. Parameter estimation formulas arederived. A method for verifying the hypothesis on the membership of a sample to the classof ALM-distributions is developed. Algorithms for computing critical levels and power of thelikelihood ratio test by the Monte Carlo method are designed.

AB - Certain characterization properties of time-varying periodic Poisson &fllig;ows are studiedin terms of almost-lack-of-memory (ALM) distributions. Parameter estimation formulas arederived. A method for verifying the hypothesis on the membership of a sample to the classof ALM-distributions is developed. Algorithms for computing critical levels and power of thelikelihood ratio test by the Monte Carlo method are designed.

KW - Mechanical Engineer

KW - Parameter Estimation

KW - Monte Carlo Method

KW - Likelihood Ratio

KW - System Theory

UR - https://digitalcommons.kettering.edu/mathematics_facultypubs/35

UR - https://link.springer.com/article/10.1023/B:AURC.0000044269.32890.3e

U2 - 10.1023/B:AURC.0000044269.32890.3e

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M3 - Article

VL - 65

JO - Automation and Remote Control

JF - Automation and Remote Control

ER -

Periodic Poisson Processes and Almost-lack-of-memory Distributions

Abstract

Keywords

Disciplines

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